Skip to content
1900

A Comprehensive Review of Electrochemical Hybrid Power Supply Systems and Intelligent Energy Managements for Unmanned Aerial Vehicles in Public Services

Abstract

The electric unmanned aerial vehicles (UAVs) are rapidly growing due to their abilities to perform some difficult or dangerous tasks as well as many public services including real-time monitoring, wireless coverage, search and rescue, wildlife surveys, and precision agriculture. However, the electrochemical power supply system of UAV is a critical issue in terms of its energy/power densities and lifetime for service endurance. In this paper, the current power supply systems used in UAVs are comprehensively reviewed and analyzed on the existing power configurations and the energy management systems. It is identified that a single type of electrochemical power source is not enough to support a UAV to achieve a long-haul flight; hence, a hybrid power system architecture is necessary. To make use of the advantages of each type of power source to increase the endurance and achieve good performance of the UAVs, the hybrid systems containing two or three types of power sources (fuel cell, battery, solar cell, and supercapacitor,) have to be developed. In this regard, the selection of an appropriate hybrid power structure with the optimized energy management system is critical for the efficient operation of a UAV. It is found that the data-driven models with artificial intelligence (AI) are promising in intelligent energy management. This paper can provide insights and guidelines for future research and development into the design and fabrication of the advanced UAV power systems.

Funding source: This work is supported in part by the founding of state key laboratory of industrial control technology, Zhejiang University (ICT2021B19), the Technological Innovation and Application Demonstration in Chongqing (Major Themes of Industry: cstc2019jscx-zdztzxX0033, cstc2019jscxfxyd0158) and the National Natural Science Foundation of China (NO. 22005026, 21908142).
Related subjects: Applications & Pathways
Loading

Article metrics loading...

/content/journal5605
2022-06-18
2024-04-29
http://instance.metastore.ingenta.com/content/journal5605
Loading
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error